2026 Jens Lagergren: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	35	11657	11324	88	86	94	5563

Overview

Jens Lagergren is a researcher affiliated with the Royal Institute of Technology in Sweden. Their work spans key areas within Biochemistry, Genetics and Molecular Biology, alongside contributions to Computer Science.

The scientist has authored numerous papers with significant focus on topics such as:

Single-cell and spatial transcriptomics
Cancer Genomics and Diagnostics
Gene expression and cancer classification
Genomics and Phylogenetic Studies
Bioinformatics and Genomic Networks
Bayesian Methods and Mixture Models
T-cell and B-cell Immunology

Among recent publications are:

Spatial transcriptomics of B cell and T cell receptors reveals lymphocyte clonal dynamics (2023, Science)
Clonally heritable gene expression imparts a layer of diversity within cell types (2024, Cell Systems)
DeepMP: a deep learning tool to detect DNA base modifications on Nanopore sequencing data (2021, Bioinformatics)
Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data (2023, Genome Biology)
Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction (2022, Proceedings of the National Academy of Sciences)

Lagergren collaborates frequently with a set of co-authors, including:

Hosein Toosi
Jeff E. Mold
Xinsong Chen
Johan Hartman
Camilla Engblom

Research outputs are commonly published in venues such as:

bioRxiv (Cold Spring Harbor Laboratory)
arXiv (Cornell University)
Bioinformatics
Nature Communications
PLoS Computational Biology

Their work addresses subfields including Molecular Biology, Cancer Research, Artificial Intelligence, Immunology, and Computer Vision and Pattern Recognition. This interdisciplinary approach highlights integration of computational techniques with molecular and cancer biology research.

Best Publications

Easy problems for tree-decomposable graphs

Stefan Arnborg;Jens Lagergren;Detlef Seese

1119
Citations
Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity

Emelie Berglund;Jonas Maaskola;Niklas Schultz;Stefanie Friedrich

586
Citations
On the Hardness of Approximating Max k-Cut and its Dual.

Viggo Kann;Sanjeev Khanna;Jens Lagergren;Alessandro Panconesi

230
Citations
Bayesian gene/species tree reconciliation and orthology analysis using MCMC

Lars Arvestad;Ann-Charlotte Berglund;Jens Lagergren;Bengt Sennblad

226
Citations
Simultaneous Bayesian gene tree reconstruction and reconciliation analysis.

Örjan Åkerborg;Bengt Sennblad;Lars Arvestad;Jens Lagergren

203
Citations
Efficient algorithms for lateral gene transfer problems

M. T. Hallett;J. Lagergren

197
Citations
Simultaneous Identification of Duplications and Lateral Gene Transfers

Ali Tofigh;Michael Hallett;Jens Lagergren

195
Citations
Gene tree reconstruction and orthology analysis based on an integrated model for duplications and sequence evolution

Lars Arvestad;Ann-Charlotte Berglund;Jens Lagergren;Bengt Sennblad

166
Citations
New algorithms for the duplication-loss model

M. T. Hallett;J. Lagergren

163
Citations
Identification of functional clusters of transcription factor binding motifs in genome sequences: the MSCAN algorithm.

Öjvind Johansson;Wynand Alkema;Wyeth W. Wasserman;Jens Lagergren

127
Citations
Genome-wide survey for biologically functional pseudogenes.

Örjan Per Svensson;Lars Arvestad;Jens Lagergren

109
Citations
New probabilistic network models and algorithms for oncogenesis.

Marcus Hjelm;Mattias Höglund;Jens Lagergren

109
Citations
A Bayesian method for analyzing lateral gene transfer.

Joel Sjöstrand;Joel Sjöstrand;Ali Tofigh;Vincent Daubin;Lars Arvestad;Lars Arvestad

108
Citations
Problems Easy for Tree-Decomposable Graphs (Extended Abstract)

Stefan Arnborg;Jens Lagergren;Detlef Seese

107
Citations
The gene evolution model and computing its associated probabilities

Lars Arvestad;Jens Lagergren;Bengt Sennblad

105
Citations
Simultaneous identification of duplications and lateral transfers

Mike Hallett;Jens Lagergren;Ali Tofigh

99
Citations
Fast neighbor joining

Isaac Elias;Jens Lagergren

91
Citations
MSCAN: identification of functional clusters of transcription factor binding sites

Wynand B.L. Alkema;Öjvind Johansson;Jens Lagergren;Wyeth W. Wasserman

89
Citations
Efficient parallel algorithms for tree-decomposition and related problems

J. Lagergren

89
Citations
Finding minimal forbidden minors using a finite congruence

Jens Lagergren;Stefan Arnborg

88
Citations
Problems Easy for Tree-Decomposable Graphs

Stefan Arnborg;Jens Lagergren;Detlef Seese

8
Citations

Frequent Co-Authors

Alessandro Panconesi Sapienza University of Rome

Nuria Lopez-Bigas Institució Catalana de Recerca i Estudis Avançats

Benny Chor Tel Aviv University

Johan Håstad Royal Institute of Technology

Sampsa Hautaniemi University of Helsinki

Niko Beerenwinkel ETH Zurich

Abel Gonzalez-Perez Pompeu Fabra University

Wyeth W. Wasserman University of British Columbia

Joakim Lundeberg Royal Institute of Technology

Simon Heath Pompeu Fabra University

External Links

Personal website of Jens Lagergren Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Exploring Computer Science opens doors to a broad range of related degrees and career trajectories. If you're interested in blending data analysis and technology, the data science learning path is a popular choice. Data science skills are in high demand, and studying online can be both flexible and affordable.

For those drawn to the hardware and systems side, accredited online electrical engineering programs offer a solid foundation. These programs give you the technical expertise to work in areas like robotics, communications, and electronics—all closely linked with computer science.

If quick career advancement is your priority, consider certificate programs that pay well. Many tech certifications can be achieved in less time than a full degree, often leading to lucrative roles in IT, cybersecurity, or programming.

Additionally, some students opt for the fastest online master's degree options. Accelerated master’s programs can help you deepen your expertise and get ahead in your career in as little as one year.